Institute of Information Theory and Automation

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Ing. Adam Novozámský, Ph.D.

Research interests: 
I am deeply immersed in Image Processing for over 12 years and I still enjoy it because each problem has its individual solution. There is always something new to discover. My research interests are: Image Processing & Deep Learning for Computer Vision, Image Forensics and Biological imaging. H-INDEX = 4 CITATIONS = 49 IN SCOPUS
Publications ÚTIA: 

I am currently a project assistant at the Computer Vision Lab (CVL) at TU Vienna and at the same time a postdoc at the Institute of Information Theory and Automation which administratively falls under the Czech Academy of Sciences. My research focuses on image analysis, medical imaging, segmentation, object detection, machine learning, and digital forensics.
I received my undergraduate degree in Computer Informatics in 2008, and a follow-up master’s program in Information Technology in 2010. In 2018 I defended my PhD in Computer Science and Applied Mathematics. All three degrees are from the Czech Technical University in PragueFaculty of Nuclear Sciences and Physical Engineering.

Curriculum-Vitae: here

PhD dissertation: here

Supervized MSc & BSc students:

[2021 - present] Research Task - Anna Gruberová : Optical Character Recognition on Scanned Historical Posters Using the State-of-the-Art Methods

Department of Software Engineering, Faculty of Nuclear Science and Physical Engineering, Czech Technical University in Prague

In progress: estimated deadline - June 2022

[2021 - present] Research Task - Soňa Drocárová : Comparison of methods for unconstrained face detection

Department of Mathematics, Faculty of Nuclear Science and Physical Engineering, Czech Technical University in Prague

In progress: estimated deadline - June 2022

[2021 - present] MSc - Adéla Kostelecká : Content-Based Image Retrieval: from Primitive to Advanced Techniques

Department of Algebra, Faculty of Mathematics and Physics, Charles University

Abstract: Today's digital age, in which almost everyone owns a mobile device with more than one camera, produces a plethora of images every day. These are then uploaded to social networks, shared, and forwarded. This increases the demand for efficient and accurate algorithms for retrieving images in the database without having to manually transcribe the scene into the metadata of each image.

In progress: estimated deadline - May 2022

[2020 - present] MSc - Roman Staněk : System for automatic size and type control of cars rims

Department of Software and Computer Science Education, Faculty of Mathematics and Physics, Charles University

In progress: estimated deadline - December 2021

[2020 - 2021] BSc - Markéta Machalová : Detection of Varroa destructor using computer vision

Department of Algebra, Faculty of Mathematics and Physics, Charles University

Abstract: The bachelor thesis deals with the design and description of a tool that can simplify the process of monitoring varroosis. Using image processing methods, it detects individual mites from the picture of the bottom board in the beehive. For better image resolution we used several images from one bottom board. Those images were then stitched into one image using image registration. In the first part we focused on the use of classical image processing methods that can detect varroa only on the basis of the approximation of the body of the mite with a parametrically descriptive curve. In the second part we used a more powerful convolutional neural network. During each of the 500 training epochs we saved the parameters of success. Finally, we inserted a test data into the trained network and compared it with expected outputs. The thesis contains a theoretical description of algorithms and methods, their use in our detector, and interpretation of results.
[ BSc thesis - CZE]      [ presentation - CZE]

[2020 - 2021] MSc - Kajetán Poliak : Hand pose estimation during car driving

Department of Mathematics, Faculty of Nuclear Science and Physical Engineering, Czech Technical University in Prague

Abstract: Hand pose estimation plays a fundamental role in human computer interactions, moreover it allows us to analyze human behavior. The problem is nontrivial due to complicated hand variations caused by complex articulations, self-occlusions or shape, size and color ambiguities. We provide complex proposal of different detection and pose estimation methods and their evaluation. The comparison of deep map and RGB based pose estimation is provided and applied to real-life data from the driving simulator. Furthermore we design an annotation tool for RGB-D data which we used to produce a test dataset.
[ MSc thesis ]      [ presentation ]

[2020 - 2021] MSc - Adam Novotný : Satellite data analysis using machine learning methods

Department of Mathematics, Faculty of Nuclear Science and Physical Engineering, Czech Technical University in Prague

Abstract: The application of machine learning, and of its subset deep learning, has improved and enabled new techniques in the domain of computer vision. Sentinel-2 mission is specifically designed to provide high-resolution optical satellite imagery, which is suitable for monitoring surface vegetation. In addition to satellite images, we are provided with agricultural field data in 2019 by State Agricultural Intervention Fund. Combining these two data sources, datasets for field crop classification into thirteen classes are prepared. Both feature-based classifiers and convolutional neural networks are then applied on these pre-processed datasets and the results of each classifier and its performance are analyzed, discussed and compared.
[ MSc thesis ]      [ presentation ]

[2019 - 2020] MSc - Dominik Vít : Automated visual inspection system for a car engine space

Department of Mathematics, Faculty of Nuclear Science and Physical Engineering, Czech Technical University in Prague

Abstract: In most automobile factories, the quality inspection process is mainly based on vision control, which is often insufficient and unstable. The artificial intelligence can improve some parts of this quality process. The aim of our project was to develop the "Proof-of-concept" of such an automated visual inspection system. We focused on the level of cooling liquid. The analysis includes data collection and labeling, pre-processing, feature extraction and classification.
[ MSc thesis ]      [ presentation ]

Grants I worked on:

Mobile diagnostic system for reduction of consumption and rational use of antibiotics for primary milk production

[2020 - 2022] Technology Agency of the Czech Republic : FW01010343

Objectives: The main objective of the project is to develop a dairy cow health control system, the ultimate goal of which would be to significantly reduce the use of antibiotics in the treatment and prevention of infectious mammary gland inflammation. Sub-goals: - Design a system of continuous microbiological diagnostics on dairy farms - Monitor the health and economic benefits of consistently applying the above system over a period of time. - Develop hardware equipment for the optical reading of color colonies of cultured microorganisms. - Develop a software solution associated with the reader to analyze the displayed microbial colonies. - Set up mutual links between the reader, its SW, the system administrator and the central database - Perform a thorough test of the whole system functionality.

project description

VKG 3.0

[2019 - 2021] Technology Agency of the Czech Republic : TH04010422

Objectives: The aim of the VKG 3.0 project is a new system for the diagnosis of vocal disorders, consisting of a new type of multi-line video camera and data processing software. The camera will allow to capture the vocal cords in a mode that detects their movement in several places at the same time, so the expert will have better idea of the vocal behavior and thus the ability to effectively make the correct diagnosis. The software for the proposed multi-line camera will be developed with the emphasis on data interpretation, special care will be devoted to the intuitive visualization of captured data. There are several features computed for each scan line. A large number of such data would not allow an effective evaluation of the finding.only the significant data will be fused.

project description

National Competence Center - Cybernetics and Artificial Intelligence

[2018 - 2020] Technology Agency of the Czech Republic : TN01000024

Objectives: The NCK KUI project aims to create a national platform for cybernetics and artificial intelligence which interlinks research and application oriented centers of robotics and cybernetics for Industry 4.0, Smart Cities, intelligent transport systems and cybersecurity. The connection of innovation leaders will raise effectivity of applied research in key areas, as advanced technology for globally competitive industry, ICT and transportation for the 21st century. NCK KUI is closely related to application sector and enables cross-domain collaboration, innovation development and technology transfer.

project description

PROVENANCE - PROviding VErificatioN AssistaNCE for New Content

[2018 - 2021] H2020-EU.2.1.1. : 825227

Objectives: PROVENANCE will develop an intermediary-free solution for digital content verification that gives greater control to users of social media and underpins the dynamics of social sharing in values of trust, openness, and fair participation. Specifically, PROVENANCE will use blockchain to record, in a secure and verifiable manner, multimedia content that is uploaded and registered by content creators or identified for registration by the PROVENANCE Social Network Monitor. The PROVENANCE Verification Layer will apply advanced tools for multimedia analytics (semantic uplift, image forensics, cascade analysis) to record any modifications to content assets and to identify similar pieces of content. A personalised Digital Companion will cater to the information needs of end-users. To help consumers navigate content and develop digital literacy competencies, an iconographic Verification Indicator will contextualise individual pieces of content with relevant information including when the content was registered, by whom, and any subsequent transactions. PROVENANCE will be co-created with diverse representatives of civil society across four distinct use-cases in the social media domain (citizen information seekers, citizen prosumers, factual content creators, and creative content creators). However, the findings will be applicable to any area in which social media and verification are important. The scientific and pragmatic insights gained through PROVENANCE will significantly advance the state of the art in intermediary-free solutions for content verification, understanding of information cascades and information sources on social media, the openness of algorithms, and user control over personal data. In so doing, it will lay the foundation for a new federated social network grounded in trust, openness, and fair participation. In addition, it will support the development of an observatory on information veracity and social media best practice under the ICT28 CSA.

project web page      project description

ASSISLT - Automated Software System In Speech-Language Therapy

[2018 - 2019] Technology Agency of the Czech Republic : TJ01000181

Objectives: The aim of our project is to create a software system to support speech therapy for adults and children with inborn and acquired motor speech disorders. The planned system focuses on individual treatment using exercises that improve tongue motion and thus articulation. The system will offer adjustable set of exercises recommended by a therapist, motivation by using augmented reality, evaluation of the performance of therapeutic movements, and session archivation. It will allow the therapist to evaluate the schedule and progress of the treatment. Linking the tongue movement and characters in a computer game will motivate children. The basic component of the system is the module evaluating the tongue motion based on image data from a commercially available camera.

project web page      project description

Automatic evaluation of videokymographic recordings for early diagnosis and prevention of vocal fold tumors

[2014 - 2017] Technology Agency of the Czech Republic : TA04010877

Objectives: The goal of the project is to develop a sophisticated software for videokymography (VKG) which will enable automatic evaluation of medical videokymographic recordings of vibrating vocal folds and arrive at correct medical diagnosis. Further goal is to develop a certified method of VKG evaluation to be used in clinical practice. VKG camera is an existing device which was developed in 1994 in collaboration of Czech and Dutch colleagues. It has been used for diagnosis of vocal fold vibration problems caused by various voice disorders, the most serious being vocal fold cancer. Currently, evaluation of VKG recordings can be done only by a highly experienced clinician. The evaluation is complicated and time-consuming. Therefore the method has not been widely used. Addition of a software for automatic evaluation will allow wider, more efficient and less time-demanding application of the method in clinical practice and an early and rather inexpensive diagnosis of tumorous states. It will allow detecting vocal fold cancer at an early stage when the treatment can be done noninvasively or by a simple surgical intervention so that the quality of life is preserved. The project is based on collaboration of four partners: clinical centre specialized in diagnosis and treatment of voice disorders (Voice Centre Prague, Medical Healthcom, Ltd), team of the inventor of the method of videokymography (dr. Svec, Department of Biophysics, Palacky University Olomouc), research institute specialized in digital image analysis (Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic) and a company experienced in diagnostic product development (STARMANS electronics).

project description

Capsule endoscopy in diagnostics of small bowel mucosal injury induced by nonsteroidal anti-inflammatory drugs

[2012 - 2015] Technology Agency of the Czech Republic : NT13532

Objectives: Prospective study is focused on identification of endoscopy, clinical and laboratory small bowel injury markers in long- term NSAID users. The patients with rheumatoid arthritis , osteoarthritis and healthy volunteers will be included into our study. The definition of the normal findings allows identification of the real NSAID induced injury. The detailed questionnaire concentrated on clinical signs will be filled with all participants. The laboratory tests and capsule endoscopy will be integral part of our study. The endoscopy findings will be scored according to the severity.

project description

Tools for imaging device identification, authentication, and image reconstruction

[2010 - 2013] Ministry of Interior : VG20102013064

Objectives: Software application, consisting of three modules for device identification, an authentication, and image reconstruction, respectively. The project output will enable an identification of the imaging device (digital cameras, camcoders), it will exclude the possibility of intentional post-processing changes of images or video. Finally, it will provide tools for quality improvement of analyzed image and video data using digital reconstruction methods.

project description

Development of methods for image analysis of photographs in digital and analog form for data authentication

[2010 - 2012] Ministry of Interior : VF20102012010

Objectives: Proposal of new software methods for image data authentication in still image record.

project description
2021-11-04 12:03

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Matematicko-fyzikální fakulta UK
Fakulta jaderná a fyzikálně-inženýrská ČVUT
Fakulta jaderná a fyzikálně-inženýrská ČVUT
Fakulta jaderná a fyzikálně-inženýrská ČVUT